King Christian in the Cold and Damp: Visual Exploration of Climate Data from Rosenborg Castle
Krarup Andersen, Cecil (1); Jänicke, Stefan (2); Sang-Hoon Lee, Daniel (1); Grinde, Andreas (3); Scharff, Mikkel (1)
1: Royal Danish Academy, Denmark; 2: University of Southern Denmark, Denmark; 3: Rosenborg Castle, Denmark
This project visualizes sensory data from Christian IV Writing Room in the Rosenborg Castle to explore ways of improving the use of climate data for better decision-making concerning risks to the paintings in the castle.
A Novel Digital Methodology for the Study of Historical Sailing Performance
Pala, Giovanni Maria (1); Costiner, Lisandra (2)
1: University of Oxford, United Kingdom; 2: Utrecht University, Netherlands
HTML XMLThis study uses 3D scans of eighteenth-century historical ship models to infer the sailing performance of their full-scale counterparts. By digitally reconstructing these models and analyzing their design and performance through engineering simulations, the proposed approach enables their comparison and facilitates the testing of existing historical narratives.
Evaluating Augmented Training Data for Complex Document Layouts: the Case of Arabic Scientific Manuscripts
Roughan, Christine
Princeton University, United States of America
HTML XMLThis short paper concerns segmentation models produced to handle complex folio layouts, here examined in the context of historical Arabic scientific manuscripts. It evaluates the efficiency of image augmentation methods at the image level and the annotated region level in producing usable segmentation models from limited training data.
Bridging the Digital with the Humanities: A Study of Embedded Faculty-Librarian Partnerships for Enhancing Humanities Research
Elayyan, Mona; Sennema, Greg; Spooner, Kevin
Wilfrid Laurier University, Canada
HTML XMLThis presentation illustrates a pedagogical effort to reimagine instruction in the humanities and political sciences. By emphasizing the importance of digital literacy as a critical component of education, it allows students to deeply engage with the changing digital landscape of academia and the technologically driven workplaces.
Modeling Errors in Estimating Historical Trends
Smith, David A.
Northeastern University, United States of America
Researchers regularly make claims about phenomena that vary over time, or with other variables of interest. Our ability to make these comparisons can be limited by “archival silences” and by the varying accuracy of digital tools. This talk compares methods for modeling the error in our estimates of historical trends.